Abstract: This research addresses the unique challenges of underwater image segmentation, such as reduced visibility, color distortion, and complex backgrounds. A key novelty of this work lies in the ...

Abstract Seamlessly blending features from multiple images is extremely challenging because of complex relationships in lighting, geometry, and partial occlusion which cause coupling between different ...

Meta Platforms Inc. today is expanding its suite of open-source Segment Anything computer vision models with the release of SAM 3 and SAM 3D, introducing enhanced object recognition and ...

The U.S. Forest Service has announced it is reversing a ban on federal firefighters wearing masks, and will give crews protective N95s as they battle increasingly intense fires across the nation. For ...

Medical image segmentation is at the heart of modern healthcare AI, enabling crucial tasks such as disease detection, progression monitoring, and personalized treatment planning. In disciplines like ...

Segmentation of Biomedical Images is based on U-Net. This U-Net implementation using Keras and TensorFlow has varying depth that can be specified by model input.

The MHSAttResDU-Net incorporates RCC for complexity control and improved generalization under varying lighting. The SSRP unit in encoder-decoder blocks reduces feature map dimensions, capturing key ...

To address the trade-off between segmentation performance and model lightweighting in computer-aided skin lesion segmentation, this paper proposes a lightweight network architecture, Multi-Conv ...